A soft measurement method for measuring coal by furnace during coal storage in the warehouse

Abstract

The present invention belongs to the field of coal quantity monitoring, involves data analysis technology, and is used to solve the problems of low accuracy level of the existing common accounting methods for coal consumption in the furnace and low efficiency of fault maintenance. Specifically, it is a soft measurement method for coal metering by furnace in the coal bin, including the following steps: conduct coal metering analysis for the raw coal bin, mark the boilers of the coal-fired power plant as the metering object i, where i = 1, 2, …, n, and n is a positive integer. The coal enters the boiler coal bin through the coal conveying trestle belt, transfer station three-way, and belt plow coal feeder above the coal bin. Mark the belts above the coal bins of the main channel and the standby channel as belt A and belt B respectively; through the coal quantity metering module, the present invention can achieve the metering function only by the soft measurement of the DCS algorithm without adding or changing on-site equipment; on the in-plant coal conveying screen, add the display parameter of the cumulative quantity of coal metering by furnace, and there is a historical record, and the coal consumption per month can be simply calculated by the difference; use pulse quantity to replace analog quantity for cumulative calculation.

Description

Technical Field

[0001] The present invention belongs to the field of coal quantity monitoring, relates to data analysis technology, and specifically is a soft measurement method for furnace-by-furnace metering of coal entering the bin. Background Art

[0002] For multiple boilers in a coal-fired power plant, coal is fed into each coal bin one by one through a common belt (assumed to be numbered #1A and #1B). The electronic belt scale for metering coal entering the furnace is installed on the common A and B belts. The coal consumption of coal entering the furnace is the most important economic index of the boiler.

[0003] The common calculation method and existing defects of the coal consumption of coal entering the furnace are automatically calculated by weighted summation of the belt scales of coal feeders. Since the calibration of the belt scales of coal feeders is restricted by the operation of the boiler, the accuracy level is not as high as that of the coal entering the bin, and only hanging weight calibration can be used. Therefore, the cumulative sum of all coal feeders can only be used as a reference for furnace-by-furnace metering. At the same time, when the coal consumption is abnormal, corresponding fault detection sequences cannot be adopted according to the overall operation state of the production line for fault repair, resulting in low efficiency of fault detection and repair.

[0004] In view of the above technical problems, this application proposes a solution. Summary of the Invention

[0005] The purpose of the present invention is to provide a soft measurement method for furnace-by-furnace metering of coal entering the bin, which is used to solve the problems of low accuracy level and low fault repair efficiency of the common calculation methods for the coal consumption of coal entering the furnace existing in the prior art;

[0006] The technical problem to be solved by the present invention is: how to provide a soft measurement method for furnace-by-furnace metering of coal entering the bin with a higher accuracy level and capable of efficiently performing fault repair.

[0007] The purpose of the present invention can be achieved by the following technical solutions:

[0008] A soft measurement method for furnace-by-furnace metering of coal entering the bin includes the following steps:

[0009] Step 1: Perform metering analysis on the coal entering the bin for the raw coal bin. Mark the boilers of the coal-fired power plant as metering objects i, where i = 1, 2,..., n, and n is a positive integer. Coal enters the boiler coal bin through the coal conveying trestle belt, transfer station three-way, and belt plow on the coal bin. Mark the belts above the coal bins of the main channel and the standby channel as belt A and belt B respectively. The cumulative flow rates of belt A and belt B are denoted as GA and GB respectively. The cumulative values of the coal entering the furnace for the metering object i are G1, G2,..., Gn;

[0010] Step 2: Monitor and analyze the cumulative coal quantity value of the metering object, set the monitoring period, mark the cumulative coal quantity values of metering object i received by the coal quantity analysis module within the monitoring period as Gi1, Gi2, …, Gim, calculate the variance of the cumulative coal quantity values from Gi1 to Gim to obtain the fluctuation coefficient BDi of the metering object, obtain the fluctuation threshold BDmax through the storage module, compare the fluctuation coefficient BDi of the metering object with the fluctuation threshold BDmax, and determine whether the coal quantity metering process during coal bin entry meets the requirements based on the comparison result;

[0011] Step 3: Conduct fault monitoring and analysis on the abnormal object, obtain the abnormal interval matching the abnormal coefficient, obtain the fault detection sequence corresponding to the abnormal interval, and sequentially conduct fault detection on the coal quantity bin entry production line according to the fault detection sequence.

[0012] As a preferred embodiment of the present invention, the process of obtaining the cumulative in-furnace coal quantity G1 of metering object 1 includes:

[0013] When the main channel belt above the raw coal bunker of metering object 1 is running and the transfer station three-way is in position A, after any plow-down signal of belt A arrives, the DCS receives the pulse signal of the electronic belt scale and starts to accumulate until the plow is lifted. The cumulative coal quantity value during this period is G1A;

[0014] When the standby channel belt above the raw coal bunker of metering object 1 is running and the transfer station three-way is in position B, after any plow-down signal of belt B arrives, the DCS receives the pulse signal of the electronic belt scale and starts to accumulate until the plow is lifted. The cumulative coal quantity value during this period is G1B;

[0015] The cumulative in-furnace coal quantity G1 of metering object 1 is obtained through the formula G1 = G1A + G1B.

[0016] As a preferred embodiment of the present invention, the cumulative in-furnace coal quantity values of metering objects 2 to n - 1 are all obtained in the same way as metering object 1. Since metering object n is located at the end of belt A and belt B at the upper part of the coal bunker and there is no coal plow, the coal quantity entering the coal bunker cannot be directly measured. Subtracting the sum of the cumulative coal quantity values of metering objects 1 to n - 1 from the total coal quantity can obtain the cumulative coal quantity value of metering object n, and the cumulative coal quantity value of metering object i is sent to the coal quantity analysis module.

[0017] As a preferred embodiment of the present invention, the fluctuation coefficient BDi is compared with the fluctuation threshold BDmax: If the fluctuation coefficient BDi is less than the fluctuation threshold BDmax, it is determined that the fluctuation of the coal quantity entering the bin of the metering object meets the requirements, and the corresponding metering object is marked as a normal object; if the fluctuation coefficient BDi is greater than or equal to the fluctuation threshold BDmax, it is determined that the fluctuation of the coal quantity entering the bin of the metering object does not meet the requirements, and the corresponding metering object is marked as an abnormal object;

[0018] Obtain the number of abnormal objects and mark the ratio of the number of abnormal objects to n as the abnormal coefficient. Obtain the abnormal threshold through the storage module, compare the abnormal coefficient with the abnormal threshold, and determine whether the coal quantity metering process for coal entering the bin meets the requirements based on the comparison result.

[0019] As a preferred embodiment of the present invention, the specific process of comparing the abnormal coefficient with the abnormal threshold includes: if the abnormal coefficient is less than the abnormal threshold, it is determined that the coal quantity metering process for the raw coal bin meets the requirements, and the coal quantity analysis module sends a signal indicating qualified coal entering the bin to the processor; if the abnormal coefficient is greater than or equal to the abnormal threshold, it is determined that the coal quantity metering process for the raw coal bin does not meet the requirements, and the coal quantity analysis module sends a signal indicating unqualified coal entering the bin to the processor. After receiving the signal indicating unqualified coal entering the bin, the processor sends the signal indicating unqualified coal entering the bin to the fault analysis module.

[0020] As a preferred embodiment of the present invention, the process of obtaining the fault detection order includes: forming an abnormal range from the maximum and minimum values of the historical abnormal coefficients received by the fault analysis module, dividing the abnormal range into several abnormal intervals, and obtaining the characteristic values of historical fault detection: when performing historical fault detection, the fault detection is carried out in the standard order. When a faulty machine is detected, the detection stops and the current detection process is marked as a fault characteristic. The standard order is S1 - S2 - S3 - S4 - S5; where S1 is the plough coal feeder detection, S2 is the electronic belt scale detection, S3 is the belt detection, S4 is the signal transmission detection, and S5 is the transfer machinery detection; sort the number of detection processes marked as fault characteristics within the abnormal interval in descending order to obtain the fault detection order, match the fault detection order with the corresponding abnormal interval, and at the same time mark the detection process ranked first as the characteristic value.

[0021] The present invention has the following beneficial effects:

[0022] 1. Through the coal quantity metering module, it is possible to achieve the metering function only by the DCS algorithm soft measurement without adding or changing on-site equipment; in the in-plant coal conveying screen, add the display parameter of the cumulative quantity of furnace-by-furnace metering, and there is a historical record, and the monthly coal consumption can be simply calculated by taking the difference; use the pulse quantity to replace the analog quantity for cumulative calculation, with high accuracy and small error;

[0023] 2. Through the coal quantity analysis module, it is possible to monitor and analyze the abnormal situation of the coal consumption quantity, feedback the abnormal degree of the coal consumption quantity through the fluctuation degree of the coal consumption within the monitoring period for the same coal inlet bin, and at the same time combine the abnormal degrees of all coal inlet bins on the production line to determine whether the coal quantity metering process for coal entering the bins on the production line is qualified, so as to determine whether to perform single detection or collective detection on the production line, providing data support for fault analysis;

[0024] 3. When the production line is abnormal, the fault analysis module can perform fault repair by adopting a corresponding fault detection sequence. The fault detection sequence is a re-shuffled and sorted standard sequence, which matches the abnormal degree of the production line with the fault type characteristics, so that the corresponding fault type characteristics can be directly found when collective abnormalities occur, and the efficiency of fault troubleshooting is much higher than the standard sequence. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0026] Figure 1 It is the system block diagram of Embodiment 1 of the present invention;

[0027] Figure 2 It is the system block diagram of Embodiment 2 of the present invention;

[0028] Figure 3 It is the method flow chart of Embodiment 3 of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0029] The following will clearly and completely describe the technical solutions of the present invention in combination with the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0030] When using the existing common accounting method for the coal consumption of coal entering the furnace for coal consumption measurement, the operating personnel manually calculate the coal feeding amount of each boiler every shift, and summarize it at the end of the month. The workload of statistics and accounting is large, and the index management personnel cannot grasp the actual situation in real time; by summing the coal belt scales of the coal entering the furnace and then taking the average value. The overall accuracy is high, but the economic indicators of each furnace cannot be independently accounted for; in order to account separately and accurately, the current method of furnace-by-furnace measurement is to adopt an additional PLC measurement device, which increases a lot of equipment and has a high failure rate.

[0031] Embodiment 1

[0032] As Figure 1 shown, a soft measurement system for furnace-by-furnace measurement of coal entering the bin includes a processor, and the processor is communicatively connected to a coal quantity measurement module, a coal quantity analysis module, a fault analysis module, and a storage module.

[0033] The coal quantity measurement module is used to measure and analyze the coal entering the raw coal bunker: Mark the boilers of coal-fired power plants as measurement objects i, where i = 1, 2, …, n, and n is a positive integer. The coal enters the boiler coal bunker through the coal conveying trestle belt, the transfer station three-way valve, and the plough coalers on the belts above the coal bunker (assumed to be numbered 2A and 2B). The dual-channel coal conveying passage includes a main channel and a standby channel. Mark the belts above the coal bunkers of the main channel and the standby channel as Belt A and Belt B respectively. Electronic belt scales are installed on both Belt A and Belt B. The instantaneous coal quantity signals of each electronic belt scale are sent to the DCS in the form of analog signals. The distributed control system is a new generation of instrument control system based on a microprocessor, adopting the design principle of decentralized control functions, centralized display and operation, taking into account decentralized autonomy and comprehensive coordination. The distributed control system is abbreviated as DCS, and can also be directly translated as "distributed control system" or "distributed computer control system"; it adopts the basic design concept of decentralized control and centralized operation and management, and adopts a multi-layer hierarchical and cooperative autonomous structure form. Its main feature is its centralized management and decentralized control. DCS has been extremely widely used in various industries such as electric power, metallurgy, and petrochemical; the cumulative coal quantity signals are sent to the DCS in the form of pulses. The cumulative flows are respectively recorded as GA and GB. The numbers of the raw coal bunkers of measurement object i are respectively 1A, 1B, …, 1F; 2A, 2B, …, 2F; nA, nB, …, nF, and the corresponding cumulative values of the coal entering the furnace are respectively G1, G2, …, Gn; the process of obtaining the cumulative value G1 of the coal entering the furnace of measurement object 1 includes: when the main channel belt above the raw coal bunker of measurement object 1 is running, the transfer station three-way valve is in position A. After any plough-down signal of Belt A arrives, the DCS receives the pulse signal of the electronic belt scale and starts to accumulate until the plough is lifted. The cumulative coal quantity value during this period is G1A; when the standby channel belt above the raw coal bunker of measurement object 1 is running, the transfer station three-way valve is in position B. After any plough-down signal of Belt B arrives, the DCS receives the pulse signal of the electronic belt scale and starts to accumulate until the plough is lifted. The cumulative coal quantity value during this period is G1B; the cumulative value G1 of the coal entering the furnace of measurement object 1 is obtained through the formula G1 = G1A + G1B. The cumulative coal quantity values of the coal entering the furnace of measurement objects 2 to n - 1 are all obtained in the same way as measurement object 1. Since measurement object n is located at the end of Belt A and Belt B above the coal bunker and there is no plough coaler, the coal quantity entering the coal bunker cannot be directly measured. Subtracting the sum of the cumulative coal quantity values of measurement objects 1 to n - 1 from the total coal quantity can obtain the cumulative coal quantity value of measurement object n. Send the cumulative coal quantity value of measurement object i to the coal quantity analysis module; without adding or changing on-site equipment, the measurement function is realized only by the DCS algorithm soft measurement; on the in-plant coal conveying screen, add the display parameter of the cumulative quantity of sub-furnace measurement, and there is a historical record. The coal consumption per month can be simply calculated by the difference; use pulse quantity instead of analog quantity for cumulative calculation, with high precision and small error.

[0034] The coal quantity analysis module is used to monitor and analyze the cumulative coal quantity value of the metering object: set the monitoring period, mark the cumulative coal quantity values of metering object i received by the coal quantity analysis module within the monitoring period as Gi1, Gi2, …, Gim, calculate the variance of the cumulative coal quantity values from Gi1 to Gim to obtain the fluctuation coefficient BDi of the metering object, obtain the fluctuation threshold BDmax through the storage module, and compare the fluctuation coefficient BDi of the metering object with the fluctuation threshold BDmax: if the fluctuation coefficient BDi is less than the fluctuation threshold BDmax, it is determined that the volatility of the coal quantity entering the bin of the metering object meets the requirements, and the corresponding metering object is marked as a normal object; if the fluctuation coefficient BDi is greater than or equal to the fluctuation threshold BDmax, it is determined that the volatility of the coal quantity entering the bin of the metering object does not meet the requirements, and the corresponding metering object is marked as an abnormal object; obtain the number of abnormal objects and mark the ratio of the number of abnormal objects to n as the abnormal coefficient, obtain the abnormal threshold through the storage module, and compare the abnormal coefficient with the abnormal threshold: if the abnormal coefficient is less than the abnormal threshold, it is determined that the coal quantity metering process of the raw coal bin meets the requirements, and the coal quantity analysis module sends a signal of qualified coal entering the bin to the processor; if the abnormal coefficient is greater than or equal to the abnormal threshold, it is determined that the coal quantity metering process of the raw coal bin does not meet the requirements, and the coal quantity analysis module sends a signal of unqualified coal entering the bin to the processor. After receiving the signal of unqualified coal entering the bin, the processor sends the signal of unqualified coal entering the bin to the fault analysis module; monitor and analyze the abnormal situation of coal consumption, feedback the abnormal degree of coal consumption through the coal consumption fluctuation degree of the same coal inlet bin within the monitoring period, and at the same time combine the abnormal degrees of all coal inlet bins of the production line to determine whether the coal quantity metering process of the production line entering the bin is qualified, so as to determine whether to conduct single detection or collective detection on the production line, providing data support for fault analysis.

[0035] After receiving the signal of unqualified incoming warehouse, the fault analysis module conducts fault monitoring and analysis on the abnormal object: obtains the abnormal range matching the abnormal coefficient, obtains the fault detection sequence corresponding to the abnormal range, and conducts fault detection on the coal feeding production line in sequence according to the fault detection sequence. Generally speaking, there is a certain rule for the faulty machinery corresponding to the abnormal coverage range in the production line. Then, by analyzing the historical fault data, the priority ranking for fault troubleshooting can be scientifically provided, so that the fault troubleshooting can be completed in the first or second fault detection process, greatly improving the efficiency of fault repair; the process of obtaining the fault detection sequence includes: the maximum and minimum values in the historical abnormal coefficients received by the fault analysis module form the abnormal range, the abnormal range is divided into several abnormal intervals, and the characteristic values of historical fault detection are obtained: during historical fault detection, the fault detection is carried out in the standard sequence, and when the faulty machinery is detected, the detection process stops and the current detection process is marked as the fault characteristic. The standard sequence is S1 - S2 - S3 - S4 - S5; where S1 is the plough coal feeder detection, S2 is the electronic belt scale detection, S3 is the belt detection, S4 is the signal transmission detection, and S5 is the transfer machinery detection; the number of detection processes marked as fault characteristics within the abnormal interval is sorted from large to small to obtain the fault detection sequence, the fault detection sequence is matched with the corresponding abnormal interval, and at the same time, the detection process ranked first is marked as the characteristic value; when the production line is abnormal, the corresponding fault detection sequence is adopted to repair the fault. The fault detection sequence is a re-shuffled order of the standard sequence, and the abnormal degree of the production line is matched with the fault type characteristics, so that the corresponding fault type characteristics can be directly found in case of collective abnormality, and the efficiency of its fault troubleshooting is much higher than the standard sequence.

[0036] Embodiment 2

[0037] Such as Figure 2As shown in the figure, the processor is also communicatively connected to a dynamic adjustment module, which is used to monitor and analyze the success rate of fault detection for the coal feeding into the bin production line in sequence according to the fault detection order: when the production line conducts fault detection on the coal feeding into the bin production line according to the fault detection order, obtain the sorting of the detection processes with successful fault detection of each abnormal object in the fault detection order and mark it as the sequence value SX, sum and average the sequence values of all abnormal objects to obtain the sequence coefficient, establish a sequence set for the sequence values of all abnormal objects and calculate the sequence performance value of the sequence set, obtain the sequence threshold and the sequence performance threshold through the storage module, and compare the sequence coefficient and the sequence performance value with the sequence threshold and the sequence performance threshold respectively: if the sequence coefficient is less than the sequence threshold and the sequence performance value is less than the sequence performance threshold, it is determined that neither the fault detection order nor the characteristic value needs to be adjusted; if the sequence coefficient is less than the sequence threshold and the sequence performance value is greater than or equal to the sequence performance threshold, it is determined that the fault detection order needs to be adjusted, but the characteristic value does not need to be adjusted, the main fault factors of the fault detection order do not need to be adjusted, and only the secondary fault factors need to be adjusted in sequence; if the sequence coefficient is greater than or equal to the sequence threshold and the sequence performance value is less than the sequence performance threshold, it is determined that both the fault detection order and the characteristic value need to be adjusted, and the adjustment process includes: sorting the detection order in descending order according to the number of successful detection processes in this fault detection, and marking the detection process ranked first as the characteristic value; if the sequence coefficient is greater than or equal to the sequence threshold and the sequence performance value is greater than or equal to the sequence performance threshold, it is determined that both the fault detection order and the characteristic value need to be adjusted, and the adjustment process includes: the dynamic adjustment module sends the data of this fault detection to the fault analysis module, and the fault analysis module updates the fault detection order through the updated historical fault detection data; by dynamically adjusting the fault detection order, the matching degree between the fault detection order and the actual fault factors can be continuously improved, thereby continuously improving the fault repair efficiency of the production line.

[0038] Embodiment III

[0039] As Figure 3 shown, a soft measurement method for coal metering by furnace when feeding into the bin includes the following steps:

[0040] Step 1: Conduct metering analysis on the coal feeding into the bin of the raw coal bunker. Mark the boilers of the coal-fired power plant as metering objects i, where i = 1, 2,..., n, and n is a positive integer. The coal enters the boiler coal bunker through the coal conveying trestle belt, transfer station three-way, and belt plow coal feeder above the coal bunker. Mark the belts above the coal bunkers of the main channel and the standby channel as belt A and belt B respectively. The cumulative flow rates of belt A and belt B are denoted as GA and GB respectively, and the cumulative values of the coal entering the furnace of metering object i are G1, G2......Gn;

[0041] Step 2: Monitor and analyze the cumulative coal quantity value of the metering object, set the monitoring period, mark the cumulative coal quantity values of metering object i received by the coal quantity analysis module within the monitoring period as Gi1, Gi2, …, Gim, calculate the variance of the cumulative coal quantity values from Gi1 to Gim to obtain the fluctuation coefficient BDi of the metering object, obtain the fluctuation threshold BDmax through the storage module, compare the fluctuation coefficient BDi of the metering object with the fluctuation threshold BDmax, and determine whether the coal quantity metering process into the warehouse meets the requirements based on the comparison result;

[0042] Step 3: Conduct fault monitoring and analysis on the abnormal object, obtain the abnormal interval matching the abnormal coefficient, obtain the fault detection sequence corresponding to the abnormal interval, and sequentially conduct fault detection on the coal quantity into the warehouse production line according to the fault detection sequence.

[0043] A soft measurement method for furnace-by-furnace metering of coal into the warehouse. During operation, conduct metering analysis on the coal into the raw coal bunker, mark the boilers of the coal-fired power plant as metering objects. The coal passes through the coal conveying trestle belt, transfer station three-way, and belt plow coal feeder above the coal bunker into the boiler coal bunker. Mark the belts above the coal bunkers of the main channel and the standby channel as Belt A and Belt B respectively, and record the cumulative flow rates of Belt A and Belt B as GA and GB respectively; Monitor and analyze the cumulative coal quantity value of the metering object, set the monitoring period, calculate the variance of the cumulative coal quantity values from Gi1 to Gim to obtain the fluctuation coefficient BDi of the metering object, obtain the fluctuation threshold BDmax through the storage module, compare the fluctuation coefficient BDi of the metering object with the fluctuation threshold BDmax, and determine whether the coal quantity metering process into the warehouse meets the requirements based on the comparison result; Conduct fault monitoring and analysis on the abnormal object, obtain the abnormal interval matching the abnormal coefficient, obtain the fault detection sequence corresponding to the abnormal interval, and sequentially conduct fault detection on the coal quantity into the warehouse production line according to the fault detection sequence.

[0044] The above content is only an example and explanation of the structure of the present invention. Those skilled in the art of this technology can make various modifications, supplements, or use similar methods to replace the specific embodiments described, as long as they do not deviate from the structure of the invention or exceed the scope defined by this claim book, they should all belong to the protection scope of the present invention.

[0045] In the description of this specification, the description referring to terms such as "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0046] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific embodiments only. Obviously, many modifications and variations can be made according to the content of this specification. These embodiments are selected and specifically described in this specification in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can well understand and utilize the present invention. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. A soft measurement method for measuring coal entering the furnace by bin Characterized in that, It includes the following steps: Step 1: Conduct a measurement analysis of the coal entering the bin of the raw coal bin. Mark the boilers of the coal-fired power plant as the measurement object i, where i = 1, 2,..., n, and n is a positive integer. The coal enters the boiler coal bin through the belt of the coal conveying trestle, the three-way of the transfer station, and the belt plough on the top of the coal bin. Mark the belts on the top of the coal bin of the main channel and the standby channel as belt A and belt B respectively. The cumulative flow rates of belt A and belt B are recorded as GA and GB respectively, and the cumulative values of the coal entering the furnace of the measurement object i are G1, G2,..., Gn; Step 2: Monitor and analyze the cumulative coal quantity values of the measurement objects. Set the monitoring period. Mark the cumulative coal quantity values of the measurement object i received by the coal quantity analysis module within the monitoring period as Gi1, Gi2,..., Gim. Calculate the variance of the cumulative coal quantity values from Gi1 to Gim to obtain the fluctuation coefficient BDi of the measurement object. Obtain the fluctuation threshold BDmax through the storage module. Compare the fluctuation coefficient BDi of the measurement object with the fluctuation threshold BDmax and determine whether the coal quantity measurement process entering the bin meets the requirements based on the comparison result; Compare the fluctuation coefficient BDi with the fluctuation threshold BDmax: If the fluctuation coefficient BDi is less than the fluctuation threshold BDmax, it is determined that the volatility of the coal quantity entering the bin of the measurement object meets the requirements, and the corresponding measurement object is marked as a normal object; If the fluctuation coefficient BDi is greater than or equal to the fluctuation threshold BDmax, it is determined that the volatility of the coal quantity entering the bin of the measurement object does not meet the requirements, and the corresponding measurement object is marked as an abnormal object; Obtain the number of abnormal objects and mark the ratio of the number of abnormal objects to n as the abnormal coefficient. Obtain the abnormal threshold through the storage module. Compare the abnormal coefficient with the abnormal threshold and determine whether the coal quantity measurement process entering the bin meets the requirements based on the comparison result; Step 3: Conduct a fault monitoring analysis of the abnormal objects. Obtain the abnormal interval matching the abnormal coefficient, obtain the fault detection sequence corresponding to the abnormal interval, and sequentially conduct fault detection on the coal quantity entering the bin production line according to the fault detection sequence; The process of obtaining the fault detection sequence includes: The maximum and minimum values of the historical abnormal coefficients received by the fault analysis module form the abnormal range. Divide the abnormal range into several abnormal intervals. Obtain the characteristic values of historical fault detection: Conduct fault detection in the standard order during historical fault detection. Stop when a faulty machine is detected and mark the current detection process as the fault characteristic. The standard order is S1 - S2 - S3 - S4 - S5; where S1 is the plough detection, S2 is the electronic belt scale detection, S3 is the belt detection, S4 is the signal transmission detection, and S5 is the transfer machinery detection. Sort the number of detection processes marked as fault characteristics within the abnormal interval from largest to smallest to obtain the fault detection sequence. Match the fault detection sequence with the corresponding abnormal interval, and at the same time mark the first detection process in the sorting as the characteristic value.

2. A soft measurement method for measuring coal entering the furnace by bin according to claim 1, Characterized in that, The process of obtaining the cumulative value G1 of the coal fed into the furnace for Measurement Object 1 includes: When the main channel belt above the raw coal bunker of Measurement Object 1 is running, the transfer station three-way valve is in position A. After any plow-down signal of Belt A is in place, the DCS receives the pulse signal of the electronic belt scale and starts to accumulate until the plow is lifted. The cumulative coal quantity value of Measurement Object 1 on Belt A is G1A. When the standby channel belt above the raw coal bunker of Measurement Object 1 is running, the transfer station three-way valve is in position B. After any plow-down signal of Belt B is in place, the DCS receives the pulse signal of the electronic belt scale and starts to accumulate until the plow is lifted. The cumulative coal quantity value of Measurement Object 1 on Belt B is G1B. The cumulative value G1 of the coal fed into the furnace for Measurement Object 1 is obtained through the formula G1 = G1A + G1B.

3. A soft measurement method for measuring coal into the bunker by furnace according to claim 2, characterized in that The cumulative coal quantity values of the coal fed into the furnace for Measurement Objects 2 to n - 1 are all obtained in the same way as that of Measurement Object 1. Since Measurement Object n is located at the end of Belt A and Belt B at the upper part of the coal bunker and there is no coal plow, the coal quantity entering the coal bunker cannot be directly measured. Subtracting the sum of the cumulative coal quantity values of Measurement Objects 1 to n - 1 from the total coal quantity can obtain the cumulative coal quantity value of Measurement Object n, and the cumulative coal quantity value of Measurement Object i is sent to the coal quantity analysis module.

4. A soft measurement method for measuring coal into the bunker by furnace according to claim 1, characterized in that The specific process of comparing the abnormality coefficient with the abnormality threshold includes: if the abnormality coefficient is less than the abnormality threshold, it is determined that the coal quantity measurement process for the coal entering the bunker of the raw coal bunker meets the requirements, and the coal quantity analysis module sends a qualified signal for coal entering the bunker to the processor; if the abnormality coefficient is greater than or equal to the abnormality threshold, it is determined that the coal quantity measurement process for the coal entering the bunker of the raw coal bunker does not meet the requirements, and the coal quantity analysis module sends an unqualified signal for coal entering the bunker to the processor. After receiving the unqualified signal for coal entering the bunker, the processor sends the unqualified signal for coal entering the bunker to the fault analysis module.

Images